23 Oct 2023
 | 23 Oct 2023
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Bayesian Inference-Based Estimation of Hourly Primary and Secondary Organic Carbon at Suburban Hong Kong: Multi-temporal Scale Variations and Evolution Characteristics during PM2.5 episodes

Shan Wang, Kezheng Liao, Zijing Zhang, Yuk Ying Cheng, Qiongqiong Wang, Hanzhe Chen, and Jian Zhen Yu

Abstract. Observation-based data of primary and secondary organic carbon in ambient particulate matter (PM) are essential for model evaluation, climate and air quality research, health effects assessment, and mitigation policy development. Since there are no direct measurement tools available to quantify primary organic (POC) and secondary organic carbon (SOC) as separate quantities, their estimation relies on inference approaches using relevant measurable PM constituents. In this study, we measured hourly carbonaceous components and major ions in PM2.5 for a year and a half in suburban Hong Kong from July 2020 to December 2021. We differentiated POC and SOC using a novel Bayesian inference approach, with sulfate identified as the most suitable SOC tracer. The hourly POC and SOC data allowed us to examine temporal characteristics varying from diurnal and weekly patterns to seasonal variations, as well as their evolution characteristics during individual PM2.5 episodes. A total of 65 city-wide PM2.5 episodes were identified throughout the entire studied period, with SOC contributions during individual episodes varying from 10 % to 66 %. In summertime typhoon episodes, elevated SOC levels were observed during daytime hours, and high temperature and NOx levels were identified as significant factors contributing to episodic SOC formation. Winter haze episodes exhibited high SOC levels, likely due to persistent influences from regional transport originating from the northern region to the sampling site. Enhanced SOC formation was observed with the increase in nocturnal NO3 radical (represented by [NO2][O3]) under conditions of high water content and strong acidity. This suggests that aqueous-phase reactions involving NO3 radical were likely a notable contributor to SOC formation during winter haze episodes. The methodology employed in this study for estimating POC and SOC provides practical guidance for other locations with similar monitoring capabilities in place. The availability of hourly POC and SOC data is invaluable for evaluating and improving atmospheric models, as well as understanding the evolution processes of PM pollution episodes. This, in turn, leads to more accurate model predictions and a better understanding of the contributing sources and processes.

Shan Wang et al.

Status: open (until 01 Jan 2024)

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  • RC1: 'Comment on egusphere-2023-2286', Anonymous Referee #1, 17 Nov 2023 reply

Shan Wang et al.


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Short summary
In this work, hourly primary and secondary organic carbon were estimated by a novel Bayesian inference approach in suburban Hong Kong. Their multi-temporal scale variations and evolution characteristics during PM2.5 episodes were examined. The methodology could serve as a guide for other locations with similar monitoring capabilities. The observation-based results are helpful for understanding the evolving nature of secondary organic aerosols and refining the accuracy of model simulations.